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- Tasks: Design and build innovative data pipelines for AI-driven trading solutions.
- Company: Join a pioneering team in financial services redefining AI and cloud-native platforms.
- Benefits: Competitive salary, creative freedom, and the chance to make a direct impact.
- Other info: Be part of a small, high-impact team with excellent career growth opportunities.
- Why this job: Shape the future of trading with cutting-edge technology and collaborate with top talent.
- Qualifications: 5-10 years in data engineering, strong Python skills, and experience with AWS.
The predicted salary is between 36000 - 60000 £ per year.
Join a pioneering team that’s redefining how AI and cloud-native platforms power front-office trading. We’re hiring a hands-on Data Engineer to help shape the future of our platform, a critical infrastructure that supports Quantitative and Strat developers in building next-generation trading solutions.
This is not a standard engineering role. You’ll work closely with front-office traders and quantitative developers, focusing on the data engineering required to design, build, and operate bespoke generative AI and agent-based systems used directly in trading workflows. The work you do will have a measurable impact on how strategies are developed, tested, and executed. If you’re motivated by building novel, production-grade systems at the leading edge of technology, this role gives you the scope to do exactly that.
What You’ll Do
- You’ll design, build, and innovate across both cloud and on-prem environments, scaling platform capabilities and driving AI adoption:
- Design, build, and maintain robust data pipelines for batch and streaming workloads, ensuring high data quality, reliability, and observability across cloud and on-prem platforms.
- Model, store, and serve large-scale datasets optimised for analytics, machine learning, and low-latency consumption by AI-driven trading systems.
- Build and optimise real-time and near-real-time data pipelines using Databricks and streaming technologies to ingest, process, and serve high-volume market and trading data at scale.
- Design and implement secure, cost-aware, scalable systems using AWS services and Kubernetes.
- Contribute to best practices for agent-based system infrastructure and mentor junior engineers when needed.
- Work across organisational boundaries and champion modern engineering trends.
- Stay ahead of the curve in agent-based systems, AI infrastructure, and cloud-native tooling.
- Architect and develop cutting-edge platform services for AI-driven trading.
Tech Stack
- Programming: Python
- AWS: S3, Kinesis, Glue, Lambda, Step Functions, SageMaker, and Databricks
- On-Prem: Managed Kubernetes Platform and Hadoop ecosystem.
What we are looking for
- ~5 – 10 years of experience in data engineering, ideally in platform or infra roles.
- ~ Strong programming skills in Python; passion for code quality and testing.
- ~ Experience with Databricks or similar tools.
- ~ Experience with AWS services (S3, Glue, Kinesis, Lambda, ECS, IAM, KMS, API Gateway, Step Functions, MSK, CloudFormation).
- ~ Experience working in a fast-paced environment in either engineering or analytical roles.
- ~ Passion for being hands-on and contributing to a collaborative engineering culture.
- ~ Direct Impact: Be part of a team building agent-based systems that traders and quants use daily to optimise strategies.
- ~ Creative Freedom: Open collaboration and the chance to bring your ideas to life.
- ~ Visibility: Be a big player in a small, high-impact team with exposure across the organisation.
Nice to Have
- Experience with on-prem Hadoop and Kubernetes.
- Familiarity with AWS cost management and optimisation tools.
- Knowledge of front-office developer workflows in financial services.
AI Data Engineer - Financial Services employer: Caspian One
Contact Detail:
Caspian One Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Data Engineer - Financial Services
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the field. Building relationships can open doors that a CV just can’t.
✨Show Off Your Skills
Don’t just tell them what you can do; show them! Create a portfolio of projects that highlight your data engineering skills, especially with Python and AWS. This will give you an edge and make you memorable.
✨Ace the Interview
Prepare for technical interviews by brushing up on your coding skills and understanding the tech stack mentioned in the job description. Practice common data engineering problems and be ready to discuss your past experiences in detail.
✨Apply Through Our Website
We encourage you to apply directly through our website! It shows your enthusiasm and gives us a chance to see your application in the best light. Plus, it’s the quickest way to get noticed by our hiring team.
We think you need these skills to ace AI Data Engineer - Financial Services
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your data engineering experience, especially with Python and AWS, to show us you’re the right fit for our pioneering team.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re excited about this role. Share specific examples of how you've designed and built data pipelines or worked with AI systems, so we can see your passion and expertise shine through.
Showcase Your Projects: If you’ve worked on relevant projects, don’t hold back! Include links to your GitHub or any other portfolio where we can see your hands-on work with data engineering and cloud technologies. We love seeing what you can do!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to shape the future of trading technology.
How to prepare for a job interview at Caspian One
✨Know Your Tech Stack
Make sure you’re well-versed in the tech stack mentioned in the job description. Brush up on your Python skills and get familiar with AWS services like S3, Kinesis, and Glue. Being able to discuss how you've used these tools in past projects will show that you're not just a fit for the role but also passionate about the technology.
✨Understand the Business Context
Since this role is closely tied to front-office trading, take some time to understand how data engineering impacts trading strategies. Familiarise yourself with concepts like agent-based systems and how they are used in financial services. This knowledge will help you connect your technical skills to real-world applications during the interview.
✨Prepare for Hands-On Questions
Expect practical questions or even coding challenges related to building data pipelines or optimising systems. Practice solving problems that involve batch and streaming workloads, as well as using Databricks. Being prepared to demonstrate your hands-on experience will set you apart from other candidates.
✨Show Your Collaborative Spirit
This role emphasises collaboration with traders and quants, so be ready to discuss your experience working in teams. Share examples of how you've mentored junior engineers or contributed to a collaborative culture. Highlighting your ability to work across organisational boundaries will resonate well with the interviewers.